Short-term guidance algorithm on a drone road system

Unmanned Aerial Vehicles (UAVs), commonly known as drones, have experienced expanding use in urban environments in recent years. However, the growing density of drones raises significant challenges, such as avoiding collisions and managing air traffic efficiently, especially in congested areas. To address these issues, a structured drone road system (DRS) and an effective guidance algorithm are essential. In this paper, we focus on the guidance aspect and propose a novel short-term decentralized greedy (STDG) algorithm designed to operate within a DRS framework. The algorithm uses only the position and speed information of nearby drones —- communicated via periodically transmitted beacons —- to make real-time decisions such as stopping, changing lanes, or adjusting speed for the next few seconds. Unlike existing methods that rely on centralized coordination, our algorithm enables drones to operate independently while ensuring safety and efficiency. We present simulation results showing the impact of key wireless and algorithm parameters on performance metrics like the drone collision rate, average speed and throughput of the drone road system.